260 research outputs found

    Quadruped Pupper Robotics: Dynamics and Control

    Get PDF
    The purpose of this project is to provide insights on the Pupper Robot, from Hands-On Robotics (handsonrobotics.org), for future studies and research. The Hands-On Robotics (HOR) team aims to provide robotics kits and educational curricula to explore agile locomotion, motor control, and AI for community colleges and high schools. We worked with the HOR team in this project to help them better achieve their goals. The main objectives of this project include: 1. Build the robot and analyze the dynamical behaviors of the robot. 2. Investigate the robot control from both hardware and software perspectives. 3. Design a new gait for the Pupper Robot. 4. Create an implementation guide for future groups, documenting knowledge we have learned during the project. By the end of this project, we achieved the following: A. Built a fully functioning robot. B. Investigated the theoretical underpinnings of quadruped robots, including inverse kinematics and gait generation theories. C. Understood and reflected on the control structure of the robot. D. Implemented a new jumping gait which allows the robot to leap forward and land on balance. E. Composed detailed guides on robot building instructions, controller files installation, simulator installation, and simulator modifications

    Master of Science

    Get PDF
    thesisThis research studies the passive dynamics of an under-actuated trotting quadruped. The goal of this project is to perform three-dimensional (3D) dynamic simulations of a trotting quadruped robot to find proper leg configurations and stiffness range, in order to achieve stable trotting gait. First, a 3D simulation framework that includes all the six degrees of freedom of the body is introduced. Directionally compliant legs together with different leg configurations are employed to achieve passive stability. Compliant legs passively support the body during stance phase and during flight phase a motor is used to retract the legs. Leg configurations in the robot's sagittal and frontal plane are introduced. Numerical experiments are conducted to search the design space of the leg, focusing on increasing the passive stability of the robot. Increased stability is defined as decreased pitching, rolling, and yawing motion of the robot. The results indicate that optimized leg parameters can guarantee passive stable trotting with reduced roll, pitch, and yaw. Studies suggest that a quadruped robot with compliant legs is dynamically stable while trotting. Results indicate that the robot based on a biological model (i.e., caudal inclination of humeri and cranial inclination of femora) has the best performance. Stiff springs at hips and shoulders, soft spring at knees and elbows, and stiff springs at ankles and wrists are recommended. The results of this project provide a conceptual framework for understanding the movements of a trotting quadruped

    Master of Science

    Get PDF
    thesisAdvances in the field of robotics have laid a solid foundation for human-robot-interaction research; this research values demonstrations of emotional competence from robotic systems and herein lie opportunities for progress within the therapeutic industry, creation of companion robots, and integration of robotics among everyday households. The development of emotive expression within robotics is progressing at a fair pace; however, there is next to no research on this form of expression as it pertains to a robot's manner of walking. The work presented here proves that it is possible for robots to walk with the capability of expressing emotions that are identifiable by their human counterparts. This hypothesis is explored utilizing a four-legged robot in simulation and reality, and the details necessary for this application are presented in this work. This quadruped is comprised of four manipulators each consisting of seven degrees of freedom. The inverse kinematics and dynamics are solved for each leg with closed form solutions that incorporate the inverse of Euler's finite rotation formula. With the kinematics solved, the robot utilizes a central pattern generator to create a neutral gait and balances with an augmented center of pressure that closely resembles the zero moment point algorithm. Independent of the kinematics, a method of generating poses that represent the emotions: happy, sad, angry, and fearful, is presented. This work also details how to overlay poses atop a gait to transform the neutral gait into an emotive walking style. In addition to laying the framework for developing the emotive walking styles, an evaluation of the presented gaits is detailed. Two IRB approved studies were performed independently of each other. The first study took feedback from subjects regarding ways to make the emotive gaits more compelling and applied them to the initial poses. The second study evaluated the effectiveness of the final gaits, with improved poses, and proves that emotive walking patterns were created; walking patterns that will be suitable for emotional acuity

    Towards the Design and Evaluation of Robotic Legs of Quadruped Robots

    Get PDF
    Legged systems have potentials of better mobility than traditional wheeled and tracked vehicles on rough terrain. The reason for the superior mobility of legged systems has been studied for a long period and plenty of robots using legs for locomotion have been developed during recent few decades. However the built legged robots still exhibit insufficiency of expected locomotive ability comparing with their counterparts in nature with similar size. The reason may be complicated and systematic associated with several aspects of the development such as the design, key components, control & planning and/or test and evaluation. The goal of this thesis is to close the gap between legged robots research & development and practical application and deployment. The research presented in this thesis focuses on three aspects including morphological parameters of quadruped robots, optimal design for knee joint mechanism and the development of a novel test bench\u2014 Terrain Simulator Platform. The primary motivation and target for legged robots developing is to overcome the challenging terrain. However few legged robots take the feature of terrain into consideration when determining the morphological parameters, such as limb length and knee orientation for robots. In this thesis, the relationship between morphological parameters of quadruped robots and terrain features are studied by taking a ditch/gap as an example. The influence of diverse types of morphological parameters including limb length, limb mass, the center-of-mass position in limbs and knee configuration on the ditch crossing capability are presented. In order to realize extended motion range and desired torque profile, the knee joint of HyQ2max adopts a six-bar linkage mechanism as transmission. Owing to the complexity of closed-loop kinematic chain, the transmission ratio is difficult to design. In this thesis, I used a static equilibrium based approach to derive the transmission relationship and study the singularity conditions. Further desired torque profile of knee joint are realized by a multi-variable geometric parameters optimization. For the test and performance evaluation of robotic leg, I designed and constructed a novel test bench\u2014 Terrain Simulator Platform (TSP). The main function of the TSP is to provide sufficient test conditions for robotic leg by simulating various terrain features. Thus working status of robotic leg can be known before the construction of the whole robot. The core of the TSP is a 3-PRR planar parallel mechanism. In this thesis, the structure design and implementation, the kinematics including singularity, workspace etc, and dynamics of this 3-PRR mechanism are presented

    In silico case studies of compliant robots: AMARSI deliverable 3.3

    Get PDF
    In the deliverable 3.2 we presented how the morphological computing ap- proach can significantly facilitate the control strategy in several scenarios, e.g. quadruped locomotion, bipedal locomotion and reaching. In particular, the Kitty experimental platform is an example of the use of morphological computation to allow quadruped locomotion. In this deliverable we continue with the simulation studies on the application of the different morphological computation strategies to control a robotic system

    ์‹ฌ์ธต ๊ฐ•ํ™”ํ•™์Šต์„ ์ด์šฉํ•œ ์‚ฌ๋žŒ์˜ ๋ชจ์…˜์„ ํ†ตํ•œ ์ดํ˜•์  ์บ๋ฆญํ„ฐ ์ œ์–ด๊ธฐ ๊ฐœ๋ฐœ

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2022. 8. ์„œ์ง„์šฑ.์‚ฌ๋žŒ์˜ ๋ชจ์…˜์„ ์ด์šฉํ•œ ๋กœ๋ด‡ ์ปจํŠธ๋กค ์ธํ„ฐํŽ˜์ด์Šค๋Š” ์‚ฌ์šฉ์ž์˜ ์ง๊ด€๊ณผ ๋กœ๋ด‡์˜ ๋ชจํ„ฐ ๋Šฅ๋ ฅ์„ ํ•ฉํ•˜์—ฌ ์œ„ํ—˜ํ•œ ํ™˜๊ฒฝ์—์„œ ๋กœ๋ด‡์˜ ์œ ์—ฐํ•œ ์ž‘๋™์„ ๋งŒ๋“ค์–ด๋‚ธ๋‹ค. ํ•˜์ง€๋งŒ, ํœด๋จธ๋…ธ์ด๋“œ ์™ธ์˜ ์‚ฌ์กฑ๋ณดํ–‰ ๋กœ๋ด‡์ด๋‚˜ ์œก์กฑ๋ณดํ–‰ ๋กœ๋ด‡์„ ์œ„ํ•œ ๋ชจ์…˜ ์ธํ„ฐํŽ˜์ด์Šค๋ฅผ ๋””์ž์ธ ํ•˜๋Š” ๊ฒƒ์€ ์‰ฌ์šด์ผ์ด ์•„๋‹ˆ๋‹ค. ์ด๊ฒƒ์€ ์‚ฌ๋žŒ๊ณผ ๋กœ๋ด‡ ์‚ฌ์ด์˜ ํ˜•ํƒœ ์ฐจ์ด๋กœ ์˜ค๋Š” ๋‹ค์ด๋‚˜๋ฏน์Šค ์ฐจ์ด์™€ ์ œ์–ด ์ „๋žต์ด ํฌ๊ฒŒ ์ฐจ์ด๋‚˜๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ์šฐ๋ฆฌ๋Š” ์‚ฌ๋žŒ ์‚ฌ์šฉ์ž๊ฐ€ ์›€์ง์ž„์„ ํ†ตํ•˜์—ฌ ์‚ฌ์กฑ๋ณดํ–‰ ๋กœ๋ด‡์—์„œ ๋ถ€๋“œ๋Ÿฝ๊ฒŒ ์—ฌ๋Ÿฌ ๊ณผ์ œ๋ฅผ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ๊ฒŒ๋” ํ•˜๋Š” ์ƒˆ๋กœ์šด ๋ชจ์…˜ ์ œ์–ด ์‹œ์Šคํ…œ์„ ์ œ์•ˆํ•œ๋‹ค. ์šฐ๋ฆฌ๋Š” ์šฐ์„  ์บก์ณํ•œ ์‚ฌ๋žŒ์˜ ๋ชจ์…˜์„ ์ƒ์‘ํ•˜๋Š” ๋กœ๋ด‡์˜ ๋ชจ์…˜์œผ๋กœ ๋ฆฌํƒ€๊ฒŸ ์‹œํ‚จ๋‹ค. ์ด๋•Œ ์ƒ์‘ํ•˜๋Š” ๋กœ๋ด‡์˜ ๋ชจ์…˜์€ ์œ ์ €๊ฐ€ ์˜๋„ํ•œ ์˜๋ฏธ๋ฅผ ๋‚ดํฌํ•˜๊ฒŒ ๋˜๋ฉฐ, ์šฐ๋ฆฌ๋Š” ์ด๋ฅผ ์ง€๋„ํ•™์Šต ๋ฐฉ๋ฒ•๊ณผ ํ›„์ฒ˜๋ฆฌ ๊ธฐ์ˆ ์„ ์ด์šฉํ•˜์—ฌ ๊ฐ€๋Šฅ์ผ€ ํ•˜์˜€๋‹ค. ๊ทธ ๋’ค ์šฐ๋ฆฌ๋Š” ๋ชจ์…˜์„ ๋ชจ์‚ฌํ•˜๋Š” ํ•™์Šต์„ ์ปค๋ฆฌํ˜๋Ÿผ ํ•™์Šต๊ณผ ๋ณ‘ํ–‰ํ•˜์—ฌ ์ฃผ์–ด์ง„ ๋ฆฌํƒ€๊ฒŸ๋œ ์ฐธ์กฐ ๋ชจ์…˜์„ ๋”ฐ๋ผ๊ฐ€๋Š” ์ œ์–ด ์ •์ฑ…์„ ์ƒ์„ฑํ•˜์˜€๋‹ค. ์šฐ๋ฆฌ๋Š” "์ „๋ฌธ๊ฐ€ ์ง‘๋‹จ"์„ ํ•™์Šตํ•จ์œผ๋กœ ๋ชจ์…˜ ๋ฆฌํƒ€๊ฒŒํŒ… ๋ชจ๋“ˆ๊ณผ ๋ชจ์…˜ ๋ชจ์‚ฌ ๋ชจ๋“ˆ์˜ ์„ฑ๋Šฅ์„ ํฌ๊ฒŒ ์ฆ๊ฐ€์‹œ์ผฐ๋‹ค. ๊ฒฐ๊ณผ์—์„œ ๋ณผ ์ˆ˜ ์žˆ๋“ฏ, ์šฐ๋ฆฌ์˜ ์‹œ์Šคํ…œ์„ ์ด์šฉํ•˜์—ฌ ์‚ฌ์šฉ์ž๊ฐ€ ์‚ฌ์กฑ๋ณดํ–‰ ๋กœ๋ด‡์˜ ์„œ์žˆ๊ธฐ, ์•‰๊ธฐ, ๊ธฐ์šธ์ด๊ธฐ, ํŒ” ๋ป—๊ธฐ, ๊ฑท๊ธฐ, ๋Œ๊ธฐ์™€ ๊ฐ™์€ ๋‹ค์–‘ํ•œ ๋ชจํ„ฐ ๊ณผ์ œ๋“ค์„ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ํ™˜๊ฒฝ๊ณผ ํ˜„์‹ค์—์„œ ๋‘˜ ๋‹ค ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์šฐ๋ฆฌ๋Š” ์—ฐ๊ตฌ์˜ ์„ฑ๋Šฅ์„ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ๋‹ค์–‘ํ•œ ๋ถ„์„์„ ํ•˜์˜€์œผ๋ฉฐ, ํŠนํžˆ ์šฐ๋ฆฌ ์‹œ์Šคํ…œ์˜ ๊ฐ๊ฐ์˜ ์š”์†Œ๋“ค์˜ ์ค‘์š”์„ฑ์„ ๋ณด์—ฌ์ค„ ์ˆ˜ ์žˆ๋Š” ์‹คํ—˜๋“ค์„ ์ง„ํ–‰ํ•˜์˜€๋‹ค.A human motion-based interface fuses operator intuitions with the motor capabilities of robots, enabling adaptable robot operations in dangerous environments. However, the challenge of designing a motion interface for non-humanoid robots, such as quadrupeds or hexapods, is emerged from the different morphology and dynamics of a human controller, leading to an ambiguity of control strategy. We propose a novel control framework that allows human operators to execute various motor skills on a quadrupedal robot by their motion. Our system first retargets the captured human motion into the corresponding robot motion with the operator's intended semantics. The supervised learning and post-processing techniques allow this retargeting skill which is ambiguity-free and suitable for control policy training. To enable a robot to track a given retargeted motion, we then obtain the control policy from reinforcement learning that imitates the given reference motion with designed curriculums. We additionally enhance the system's performance by introducing a set of experts. Finally, we randomize the domain parameters to adapt the physically simulated motor skills to real-world tasks. We demonstrate that a human operator can perform various motor tasks using our system including standing, tilting, manipulating, sitting, walking, and steering on both physically simulated and real quadruped robots. We also analyze the performance of each system component ablation study.1 Introduction 1 2 Related Work 5 2.1 Legged Robot Control 5 2.2 Motion Imitation 6 2.3 Motion-based Control 7 3 Overview 9 4 Motion Retargeting Module 11 4.1 Motion Retargeting Network 12 4.2 Post-processing for Consistency 14 4.3 A Set of Experts for Multi-task Support 15 5 Motion Imitation Module 17 5.1 Background: Reinforcement Learning 18 5.2 Formulation of Motion Imitation 18 5.3 Curriculum Learning over Tasks and Difficulties 21 5.4 Hierarchical Control with States 21 5.5 Domain Randomization 22 6 Results and Analysis 23 6.1 Experimental Setup 23 6.2 Motion Performance 24 6.3 Analysis 28 6.4 Comparison to Other Methods 31 7 Conclusion And Future Work 32 Bibliography 34 Abstract (In Korean) 44 ๊ฐ์‚ฌ์˜ ๊ธ€ 45์„
    • โ€ฆ
    corecore